Fast and reliable failure detection is crucial for damaged aircraft to maintain controlled flight. The two main objectives of the U.S. Government's Aviation Safety Program are to develop and demonstrate technologies that reduce aircraft accident rates, and develop technologies that reduce aviation injuries and fatalities when accidents do occur. Fault detection, isolation, and reconfiguration (FDIR) for flight control continues to be an active area of research in the aerospace community. To date, a wide variety of technologies have been demonstrated in high-fidelity simulations (that is, simulations with minimal distortions) and in actual flight tests with various levels of success.
For model-based aircraft fault detection, a mathematical model of the aircraft is used. Model-based fault detection is based on comparing measurements from the aircraft with corresponding error predictions from the aircraft model (that is, residual processing). In real life situations, the comparison of these signals is not trivial. This is due to the fact that (typically) there are imperfections in most mathematical flight simulation models coinciding with multiple sources of aircraft measurements errors. Therefore, any fault detection algorithms require fast and reliable processing in the presence of modeling and measurement errors.